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Abstract Medulloblastoma, the most common malignant pediatric brain tumor, is classified into four main molecular subgroups, but group 3 and group 4 tumors are difficult to subclassify and have a poor prognosis. Rapid point-of-care diagnostic and prognostic assays are needed to improve medulloblastoma risk stratification and management. N6-methyladenosine (m6A) is a common RNA modification and long non-coding RNAs (lncRNAs) play a central role in tumor progression, but their impact on gene expression and associated clinical outcomes in medulloblastoma are unknown. Here we analyzed 469 medulloblastoma tumor transcriptomes to identify lncRNAs co-expressed with m6A regulators. Using LASSO-Cox analysis, we identified a five-gene m6A-associated lncRNA signature (M6LSig) significantly associated with overall survival, which was combined in a prognostic clinical nomogram. Using expression of the 67 m6A-associated lncRNAs, a subgroup classification model was generated using the XGBoost machine learning algorithm, which had a classification accuracy > 90%, including for group 3 and 4 samples. All M6LSig genes were significantly correlated with at least one immune cell type abundance in the tumor microenvironment, and the risk score was positively correlated with CD4+ naïve T cell abundance and negatively correlated with follicular helper T cells and eosinophils. Knockdown of key m6A writer genes METTL3 and METTL14 in a group 3 medulloblastoma cell line (D425-Med) decreased cell proliferation and upregulated many M6LSig genes identified in our in silico analysis, suggesting that the signature genes are functional in medulloblastoma. This study highlights a crucial role for m6A-dependent lncRNAs in medulloblastoma prognosis and immune responses and provides the foundation for practical clinical tools that can be rapidly deployed in clinical settings.
Joshi et al. (Mon,) studied this question.
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